DSD_Gaussians
From stream v1.23
by Michael Hahsler
Mixture of Gaussians Data Stream Generator
A data stream generator that produces a data stream with a mixture of static Gaussians.
Usage
DSD_Gaussians(k=2, d=2, mu, sigma, p, separation=0.2, noise=0, noise_range)
Arguments
 k
 Determines the number of clusters.
 d
 Determines the number of dimensions.
 mu
 A matrix of means for each dimension of each cluster.
 sigma
 A list of length
k
of covariance matrices.  p
 A vector of probabilities that determines the likelihood of generated a data point from a particular cluster.
 separation
 Minimum distance between cluster centers to reduce overlap between clusters (0.8).
 noise
 Noise probability between 0 and 1. Noise is uniformly distributed within noise range (see below).
 noise_range
 A matrix with d rows and 2 columns. The first column contains the minimum values and the second column contains the maximum values for noise.
Details
DSD_Gaussians
creates a mixture of k
d
dimensional
static Gaussians in approximately unit space.
The centers mu
and the covariance matrices sigma
can be supplied or will be randomly generates. The probability vector p
defines for each cluster the probability that the next data point will
be chosen from it (defaults to equal probability).
The generation method is similar to the one suggested by Jain and Dubes (1988).
Value

Returns a
DSD_Gaussians
object (subclass of
DSD_R
, DSD
) which is a list of the defined
params. The params are either passed in from the function or
created internally. They include:References
Jain and Dubes(1988) Algorithms for clustering data, PrenticeHall, Inc., Upper Saddle River, NJ, USA.
See Also
Examples
# create data stream with three clusters in 3dimensional data space
stream1 < DSD_Gaussians(k=3, d=3)
plot(stream1)
# create data stream with specified clusterpositions,
# 20% noise in a given bounding box and
# with different densities (1 to 9 between the two clusters)
stream2 < DSD_Gaussians(k=2, d=2,
mu=rbind(c(.5,.5), c(.5,.5)),
noise=0.2, noise_range=rbind(c(1,1),c(1,1)),
p=c(.1,.9))
plot(stream2)
Community examples
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